Senior Manager, Data & Storage Reliability Engineering

Description

The company is hiring an experienced senior manager to lead its Data & Storage Reliability Engineering team.

The team covers prevention engineering, reliability, observability, incident learnings, diagnostics, automation, capacity planning, and reducing platform risk.

The work calls for deep knowledge of database and distributed systems design, large SaaS production environments, and customer-facing operations, plus people leadership and disciplined execution.

You will guide a team that spots repeating production problems and turns incident and escalation lessons into lasting engineering fixes that make the platform more resilient at scale.

Responsibilities

• Set the team's strategy for prevention, reliability, observability, resilience, and operational risk across large production environments, then carry it out.
• Turn production signals, incident lessons, customer escalations, migration results, and telemetry into lasting engineering work.
• Work closely with SWAT and Customer & Production Engineering so production operations feed back into platform improvements.
• Push forward observability, diagnostics, automation, reliability reviews, resiliency checks, migration readiness, and engineering guardrails.
• Find repeated failure patterns, reliability risks, monitoring gaps, inefficient operations, scaling limits, and performance bottlenecks, then act to cut future customer impact.
• Set reliability, resilience, observability, automation, and prevention goals for critical database and storage services.
• Promote proactive monitoring, production analytics, and automation to reduce manual work.
• Lead deep root cause analysis and make sure fixes for recurring and customer-impacting events are implemented and hold.
• Use production evidence to shape database, storage, reliability, observability, and platform architecture priorities with engineering leaders.
• Recruit, grow, and manage a strong team of reliability, prevention, observability, and platform engineers, covering careers, objectives, project priorities, onboarding, and performance reviews.
• Manage a team that supports production work, including on-call and escalation duty where needed.
• Build a culture that rejects repetitive manual work, favouring automation, self-service diagnostics, guardrails, and scalable practices.
• Lead initiatives with partner teams to improve reliability, resilience, scalability, and efficiency of the platform.
• Turn quick recovery lessons from escalations and crises into lasting prevention work.
• Review existing processes and improve them for efficiency and prevention.
• Provide training, documentation, dashboards, playbooks, and support to partner teams that work with the Data & Storage Reliability Engineering team.
• Bring new hires, technologies, systems, and automations into the team so they run smoothly and scale.

Requirements

• Have experience using AI in work processes, decision-making, or problem-solving, such as AI tools, workflow automation, analysis of AI-driven insights, or thinking through AI's effect on the function.
• Have 10+ years in database engineering, reliability engineering, distributed systems, platform, infrastructure, or production engineering, or large-scale SaaS platform operations.
• Have 4+ years of engineering leadership, including leading engineers and cross-functional or distributed teams.
• Have led Reliability, Database, Platform, Infrastructure, Production, or Performance Engineering teams, or similar technical teams.
• Bring strong expertise in database technologies, operating system performance, distributed systems, cloud-native architecture, and large production environments.
• Understand reliability engineering, observability, diagnostics, root cause analysis, capacity planning, scalability, resiliency, automation, and operational excellence.
• Have turned production insights, customer escalations, incident lessons, telemetry, and recurring operational problems into prioritized engineering work.
• Have designed or improved observability, diagnostics, reliability reviews, migration readiness checks, resiliency validation, automation, and engineering guardrails.
• Can tune and troubleshoot across database, operating system, storage, network, and application layers.
• Have a proven record of finding and fixing complex reliability, scalability, performance, efficiency, and operational bottlenecks in large distributed environments.
• Have led customer-critical investigations into reliability, capacity, performance, scalability, resilience, or operational risk.
• Have used observability and telemetry platforms to analyze system behavior and drive platform improvements.
• Have worked with software engineering, infrastructure, production operations, and escalation teams to improve reliability, scalability, efficiency, and production readiness.
• Have driven engineering initiatives using data, metrics, incident learnings, telemetry, benchmarking, and measurable results.
• Communicate well, manage stakeholders effectively, and lead with strength.
• Hold a Bachelor's degree in Computer Science, Engineering, or a related technical field, or have equivalent practical experience.
• Desired: Have operated large enterprise database and storage platforms supporting mission-critical workloads.
• Desired: Have grown Reliability, Database, Platform, Performance, Scalability, or Production Engineering teams.
• Desired: Have worked with observability platforms, telemetry systems, diagnostics frameworks, production analytics, reliability scorecards, engineering metrics, and impact reporting.
• Desired: Have run reliability reviews, resiliency validation, migration readiness, workload simulation, capacity forecasting, prevention programs, and operational risk frameworks.
• Desired: Have used AI to improve anomaly detection, forecasting, incident analysis, prioritization, operational efficiency, or engineering productivity.
• Desired: Understand distributed systems architecture, cloud platform operations, Linux production environments, and hyperscale environments.
• Desired: Have contributed to platform architecture, database strategy, reliability investment, scalability roadmaps, and long-term engineering improvements.
• Desired: Have done performance testing, benchmarking, workload simulation, and capacity modeling as part of reliability and prevention programs.
• Desired: Have supported enterprise databases such as MySQL, MariaDB, PostgreSQL, Oracle, SQL Server, or cloud-native database platforms.
• Desired: Are familiar with the company platform architecture and large-scale SaaS operations.

Conditions

Work persona is flexible, remote, or required in office, assigned based on the nature of the work and the employee's work location.

To confirm work persona eligibility, the company may use a third-party service to check the distance between your home and the nearest company office.